About the NCI Mouse Proteomic Technologies Initiative

The NCI Mouse Proteomic Technologies Initiative, a component of NCI's Clinical Proteomic Technologies for Cancer, is designed to use animal models to develop and standardize technologies that help improve the accurate measurement of proteins and peptides linked to cancer processes. Launched in 2004 with funding to two consortia, the program reflects a multidisciplinary and collaborative team approach to the development of standard tools and resources needed to accelerate protein biomarker discovery.

Goals

The goals of the Initiative are to use mouse models to:

  • Standardize methods for protein and peptide detection and analysis.
  • Develop metrics of performance and supporting reagents for promising technologies.
  • Identify or characterize new biomarkers associated with cancer processes in mouse models of human cancer.
  • Enhance current technologies for analysis of proteins and peptides in biological fluids.
  • Refine and standardize methods of specimen preparation and develop specimen reference standards.
  • Design common data elements and algorithms to facilitate data sharing among different laboratories.
  • Improve detection capabilities associated with current technologies, including sensitivity and resolution.

Structure

The Initiative has funded two consortia of laboratories: the "Eastern Consortium," based at the University of Michigan (Ann Arbor, MI) and the "Western Consortium," based at the Fred Hutchinson Cancer Research Center (Seattle, WA), to develop and standardize technologies used to identify proteins and peptides in complex mixtures.

For a complete listing of members in the Eastern and Western Consortia,
click here.

Consortia Activities

Each consortium consists of at least three laboratories that co-develop and co-evaluate multiple technologies to identify proteins in mouse models of human cancer. A total of 12 mouse models are being investigated that include breast, lung, prostate, ovarian, gastrointestinal, skin, and pancreatic cancers. Technologies evaluated include different fractionation approaches, serum and plasma analysis, and mass spectrometry and affinity-based platform analysis, such as microarrays.

Each consortium collected serum for protein measurements from inbred mouse models that represent different, well-characterized cancer tumors. Using these mouse models, the consortia employed standardized protocols to collect serum, plasma, and other biospecimens, and the results of experiments to identify and characterize proteins were cross-validated in at least two of the laboratories within the consortium.

Efforts by the Western Consortium have identified optimal proteomic methods for the reproducible analysis of serum samples. Using these optimized methods, mass spectrometric data are being generated and analyzed for models of breast, prostate, and gastrointestinal cancers.

Efforts at the Eastern Consortium have focused on gel-based fractionation followed by tandem mass spectrometric analysis for the proteomic profiling of mouse models of ovarian, breast, pancreatic, and lung cancers. In all models profiled, distinctive proteins associated with tumor progression in the mouse have been identified that include proteins previously described in corresponding human tumors and novel proteins for which there is evidence of overexpression in corresponding human tumors (based on literature, gene expression data, and immunohistochemistry).

Resources for the Consortia and for the Research Community

The two consortia have developed procedures for sharing biospecimens, reagents, and data obtained from protein measurements in the mouse models. Distribution of these resources is overseen by a coordinating center that facilitates the communication, sharing, and exchange of tools and standards between participating consortia laboratories and external laboratories. The experimental results produced by each consortium will be submitted to a publicly available, caBIG®-compatible project database managed by the NCI Center for Bioinformatics.

Resources disseminated from the program are being made available to the broader scientific community, including mouse models of human cancer, biospecimens, reagents (proteins, peptides, and antibodies), standardized protocols, and open-source proteomics software and data.

In addition, consortia teams are manufacturing monoclonal and polyclonal antibodies for characterization and use by Consortia members and, eventually, the general public.

Available resources from the consortia can be found here.

Informatics Tools

Consortia members have developed a suite of new proteomic informatics tools that permit data sharing among laboratories, including:

  • Computational Proteomics Analysis System (CPAS): An open-source, web-based proteomics data management software suite that combines laboratory information management systems (LIMS) and informatics modules for high-throughput liquid chromatography/tandem mass spectrometry (LC/MS/MS) experiments and clinical trials. CPAS enables the cancer proteomics community to store, analyze, and share clinical proteomics data. (To read more about CPAS, click here)

Several compatible modules are also available includeing:

  • msInspect: A suite of algorithms for spectral processing of high-resolution LC-MS data analysis. (To read more about msInspect, click here)
  • Q3: A suite of algorithms to assist with quantitation using isotopic labeling and high-resolution mass spectrometry.
  • PETAL: A suite of software algorithms for spectral alignment of peptide arrays.
  • X!Tandem pluggable scoring and customizable score: A flexible architecture for X!Tandem to allow configurable scoring algorithm plus a customized scoring algorithm that is compatible with Peptide Prophet.
  • PepXML converter for X!Tandem: Methods for X!Tandem to write to a standardized file format.

These software platforms and tools are available online at http://proteomics.fhcrc.org/CPL/home.html.